{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:48:00.888878Z",
     "iopub.status.busy": "2024-11-29T16:48:00.888878Z",
     "iopub.status.idle": "2024-11-29T16:48:03.356527Z",
     "shell.execute_reply": "2024-11-29T16:48:03.355524Z",
     "shell.execute_reply.started": "2024-11-29T16:48:00.888878Z"
    }
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:48:12.934922Z",
     "iopub.status.busy": "2024-11-29T16:48:12.934922Z",
     "iopub.status.idle": "2024-11-29T16:48:14.311987Z",
     "shell.execute_reply": "2024-11-29T16:48:14.310729Z",
     "shell.execute_reply.started": "2024-11-29T16:48:12.934922Z"
    }
   },
   "source": [
    "# 案例一\n",
    "泰克尼克号数据分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:53:16.621626Z",
     "iopub.status.busy": "2024-11-29T16:53:16.621626Z",
     "iopub.status.idle": "2024-11-29T16:53:16.753044Z",
     "shell.execute_reply": "2024-11-29T16:53:16.753044Z",
     "shell.execute_reply.started": "2024-11-29T16:53:16.621626Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
      "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
      "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
      "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
      "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
      "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
      "\n",
      "     who  adult_male deck  embark_town alive  alone  \n",
      "0    man        True  NaN  Southampton    no  False  \n",
      "1  woman       False    C    Cherbourg   yes  False  \n",
      "2  woman       False  NaN  Southampton   yes   True  \n",
      "3  woman       False    C  Southampton   yes  False  \n",
      "4    man        True  NaN  Southampton    no   True  \n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 891 entries, 0 to 890\n",
      "Data columns (total 15 columns):\n",
      " #   Column       Non-Null Count  Dtype   \n",
      "---  ------       --------------  -----   \n",
      " 0   survived     891 non-null    int64   \n",
      " 1   pclass       891 non-null    int64   \n",
      " 2   sex          891 non-null    object  \n",
      " 3   age          714 non-null    float64 \n",
      " 4   sibsp        891 non-null    int64   \n",
      " 5   parch        891 non-null    int64   \n",
      " 6   fare         891 non-null    float64 \n",
      " 7   embarked     889 non-null    object  \n",
      " 8   class        891 non-null    category\n",
      " 9   who          891 non-null    object  \n",
      " 10  adult_male   891 non-null    bool    \n",
      " 11  deck         203 non-null    category\n",
      " 12  embark_town  889 non-null    object  \n",
      " 13  alive        891 non-null    object  \n",
      " 14  alone        891 non-null    bool    \n",
      "dtypes: bool(2), category(2), float64(2), int64(4), object(5)\n",
      "memory usage: 80.7+ KB\n",
      "survived         0\n",
      "pclass           0\n",
      "sex              0\n",
      "age            177\n",
      "sibsp            0\n",
      "parch            0\n",
      "fare             0\n",
      "embarked         2\n",
      "class            0\n",
      "who              0\n",
      "adult_male       0\n",
      "deck           688\n",
      "embark_town      2\n",
      "alive            0\n",
      "alone            0\n",
      "dtype: int64\n",
      "     survived  pclass     sex   age  sibsp  parch     fare embarked   class  \\\n",
      "0           0       3    male  22.0      1      0   7.2500        S   Third   \n",
      "1           1       1  female  38.0      1      0  71.2833        C   First   \n",
      "2           1       3  female  26.0      0      0   7.9250        S   Third   \n",
      "3           1       1  female  35.0      1      0  53.1000        S   First   \n",
      "4           0       3    male  35.0      0      0   8.0500        S   Third   \n",
      "..        ...     ...     ...   ...    ...    ...      ...      ...     ...   \n",
      "885         0       3  female  39.0      0      5  29.1250        Q   Third   \n",
      "886         0       2    male  27.0      0      0  13.0000        S  Second   \n",
      "887         1       1  female  19.0      0      0  30.0000        S   First   \n",
      "889         1       1    male  26.0      0      0  30.0000        C   First   \n",
      "890         0       3    male  32.0      0      0   7.7500        Q   Third   \n",
      "\n",
      "       who  adult_male deck  embark_town alive  alone  \n",
      "0      man        True  NaN  Southampton    no  False  \n",
      "1    woman       False    C    Cherbourg   yes  False  \n",
      "2    woman       False  NaN  Southampton   yes   True  \n",
      "3    woman       False    C  Southampton   yes  False  \n",
      "4      man        True  NaN  Southampton    no   True  \n",
      "..     ...         ...  ...          ...   ...    ...  \n",
      "885  woman       False  NaN   Queenstown    no  False  \n",
      "886    man        True  NaN  Southampton    no   True  \n",
      "887  woman       False    B  Southampton   yes   True  \n",
      "889    man        True    C    Cherbourg   yes   True  \n",
      "890    man        True  NaN   Queenstown    no   True  \n",
      "\n",
      "[714 rows x 15 columns]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic = sns.load_dataset(\"titanic\")\n",
    "print(titanic.head())\n",
    "titanic.info()\n",
    "# 检查是否有缺失值\n",
    "print(titanic.isnull().sum())\n",
    "\n",
    "sns.set_style(\"darkgrid\")\n",
    "print(titanic[titanic['age'].notnull()])\n",
    "sns.histplot(data = titanic[titanic['age'].notnull()]['age'],kde=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:55:27.889791Z",
     "iopub.status.busy": "2024-11-29T16:55:27.888754Z",
     "iopub.status.idle": "2024-11-29T16:55:28.031528Z",
     "shell.execute_reply": "2024-11-29T16:55:28.031528Z",
     "shell.execute_reply.started": "2024-11-29T16:55:27.889791Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 把年龄的缺失值填充为平均值\n",
    "titanic['age'] = titanic['age'].fillna(titanic['age'].mean())\n",
    "sns.histplot(titanic['age'],kde=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:53:20.595246Z",
     "iopub.status.busy": "2024-11-29T16:53:20.594241Z",
     "iopub.status.idle": "2024-11-29T16:53:20.711483Z",
     "shell.execute_reply": "2024-11-29T16:53:20.711483Z",
     "shell.execute_reply.started": "2024-11-29T16:53:20.595246Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['S' 'C' 'Q' nan]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "survived         0\n",
      "pclass           0\n",
      "sex              0\n",
      "age            177\n",
      "sibsp            0\n",
      "parch            0\n",
      "fare             0\n",
      "embarked         0\n",
      "class            0\n",
      "who              0\n",
      "adult_male       0\n",
      "deck           688\n",
      "embark_town      2\n",
      "alive            0\n",
      "alone            0\n",
      "dtype: int64\n",
      "      sex   age     fare embarked  class alive  alone\n",
      "0    male  22.0   7.2500        S  Third    no  False\n",
      "1  female  38.0  71.2833        C  First   yes  False\n",
      "2  female  26.0   7.9250        S  Third   yes   True\n",
      "3  female  35.0  53.1000        S  First   yes  False\n",
      "4    male  35.0   8.0500        S  Third    no   True\n"
     ]
    }
   ],
   "source": [
    "# 1: 填充embarked数据\n",
    "print(titanic['embarked'].unique())\n",
    "# 首先会对输入的列进行分组,然后对每一组进行统计(count)，最后进行可视化 Plot\n",
    "# sns.countplot(x=titanic['embarked'],data=titanic)\n",
    "sns.countplot(y=titanic['embarked'],hue='sex',data=titanic)\n",
    "plt.show()\n",
    "# inplace=True: 则会修改操作的数据集\n",
    "titanic.fillna({'embarked':'S'},inplace=True)\n",
    "print(titanic.isnull().sum())\n",
    "\n",
    "# 2: 删除不必要的列\n",
    "titanic.drop(labels=['survived','pclass','sibsp','parch','who','adult_male','deck','embark_town'],axis=1,inplace=True)\n",
    "print(titanic.head(n=5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:54:56.433145Z",
     "iopub.status.busy": "2024-11-29T16:54:56.433145Z",
     "iopub.status.idle": "2024-11-29T16:54:56.553809Z",
     "shell.execute_reply": "2024-11-29T16:54:56.553809Z",
     "shell.execute_reply.started": "2024-11-29T16:54:56.433145Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      sex   age     fare embarked  class alive  alone\n",
      "0    male  22.0   7.2500        S  Third    no  False\n",
      "1  female  38.0  71.2833        C  First   yes  False\n",
      "2  female  26.0   7.9250        S  Third   yes   True\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1: 分析性别对存活率的影响,结论: 在事故中,女士优先,存活率高于男士\n",
    "print(titanic.head(n=3))\n",
    "sns.set_style(\"darkgrid\")\n",
    "sns.countplot(x=\"alive\",hue='sex',data=titanic)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:56:42.704915Z",
     "iopub.status.busy": "2024-11-29T16:56:42.704915Z",
     "iopub.status.idle": "2024-11-29T16:56:42.822598Z",
     "shell.execute_reply": "2024-11-29T16:56:42.822598Z",
     "shell.execute_reply.started": "2024-11-29T16:56:42.704915Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<function agelevel at 0x000002030826B8B0>\n",
      "      sex        age     fare embarked   class alive  alone age_level\n",
      "0    male  22.000000   7.2500        S   Third    no  False   midlife\n",
      "1  female  38.000000  71.2833        C   First   yes  False   midlife\n",
      "2  female  26.000000   7.9250        S   Third   yes   True   midlife\n",
      "3  female  35.000000  53.1000        S   First   yes  False   midlife\n",
      "4    male  35.000000   8.0500        S   Third    no   True   midlife\n",
      "5    male  29.699118   8.4583        Q   Third    no   True   midlife\n",
      "6    male  54.000000  51.8625        S   First    no   True   midlife\n",
      "7    male   2.000000  21.0750        S   Third    no  False     child\n",
      "8  female  27.000000  11.1333        S   Third   yes  False   midlife\n",
      "9  female  14.000000  30.0708        C  Second   yes  False     child\n"
     ]
    },
    {
     "data": {
      "image/png": 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HcAAAKCKjB46yiEnGAADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcLgPDgAARcSN/twPAQcAgCIwm03yr+wt85+e1F2S7DabMjKzihRydu3aqREjhmnz5p1/2b9w4Xz9+GOCZs2K11dfrdGiRfFavnzNX46NixsvSRo7dnyh6yluBBwAAIrAbDbJbLEofeULyk0/WuLrKxdUT0FRr8tsNpXoUZw+ffrpoYceLbH3L2kEHAAAikFu+lHlnjng6jKKjY+Pj6tLKBICDgAABnfqVLKmTZuivXt3q2JFP/Xp00/16zeQJK1evVyLFy/UxYsXdM89HTVyZKw8PT3znKL6s8TEHzV9+lSdOHFCrVtfeYp6+fLlS3WbboSrqAAAMLCcnBw9+2yMfHy8NX/+Yj333BjFx89WVlaWJGnjxg2aNm2mJk2aqo0b/6Wvvvriuu+XkZGh0aOf0R13RGrx4qWqU6euNm78V2lsSoFwBAcAAAPbseN7ZWZm6MUXX5GPTwXVq1dfzzwzSmbzlWMczz8/RrVq1Va9eg0UERGpw4eTrvt+GzZ8rcqV/fWPf4yQyWTSoEFD9f33W0pjUwqEIzgAABjYyZMnFBJSSz4+FZxt3bo9KC8vL0lSzZrBznZfX19Zrdbrvt/x48fUoMGtMpn+d1l8o0ZNi7nqoiPgAABgYB4e1z9ZY/nT5e0Ox42vzPrzkHLl3O+EkPtVBAAAik1wcC2dPp2s7Oxs50TgWbOma8eO7wv1fvXq1de2bZtls9mc4ejnnw+pevUaxVZzcSDgAABQDMoF1XPL9bRqdacCAgI1dWqc+vcfpOTkE/r88xWaMGGyRo9+psDrv/fe+7Vw4Xy9886b6t37EW3e/K327k0k4AAAYCR2u0N2m01BUa+X3jpttnzf5M/Dw0Ovvz5N06a9oSee6KvAwEBFRz9d6Mu6/fz89NZbM/Xmm5M1YMBjCg0NU6dOXfN1aqs0mRzuVlEpS0//7apzicXBw8Msf/8K6jt9rQ6ePl/8KygjGtUM0NJnuisj46IuX7a7uhwAKLTcXKvOnUtVYGB1lSvnmaePZ1EVr+vta5NJCgqqeMP34AgOAABFZPTAURZxFRUAADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADActwk4Q4YM0QsvvOB8vX//fj300EMKDQ1Vr1699NNPP+UZv3btWnXs2FGhoaGKjo7W+fM3771mAABAXm4RcL788ktt2rTJ+frSpUsaMmSIIiIitHLlSoWFhWno0KG6dOmSJGnPnj0aO3asYmJi9Omnn+rXX39VbGysq8oHANzkzGaTPDzMpfZTmjcVLIhdu3aqTZsIV5chyQ1u9JeZmakpU6aoefPmzravvvpKXl5eGj16tEwmk8aOHatvv/1W69atU1RUlJYsWaIuXbqoZ8+ekqQpU6bonnvuUXJyskJCQly0JQCAm5HZbFJlf29ZzJYbDy4mNrtNmRlZ3FzwOlwecN544w316NFDZ8+edbYlJiYqPDxcJtOVhGoymXT77bdr9+7dioqKUmJiop588knn+OrVq6tGjRpKTEwscMAxuWcINiT2NYCy7Fr/DzObTbKYLZrwzwk6nnG8xOuo419Hr3R6RWazyfABx2S6er/n97vEpQFn27Zt2rlzp9asWaPx48c729PS0tSgQYM8YwMDA5WUlCRJOnv2rKpWrXpV/5kzZwpcQ2DgjZ9ngaLz96/g6hIAoEiys7N1/rxZFsuV01G/s1iu/H4847h+Tvu51Or5fb35kZi4W7Nnz9ChQwdlMklhYeEaO/ZlBQVV0fbt2zRjxts6dSpZYWHhCg4O0aVLl/TyyxMkSatWLdcHHyxWZmaGGjVqouefH60GDW6VJF28eEGvvx6nLVu+U2BgkHr0+Lsk5dk/hWG3m2Q2X3mmY2EfCuqygJOTk6NXXnlFL7/88lXFZ2VlydMz78O1PD09ZbVaJV35R3a9/oI4d65kHrZpsZj5Uv+DjIyLstl42CaAsis31yq73S6bzeEWDw+22ez5quPChQt6/vkReuSRvho3boLS09M0adKrWrx4kR56qI9GjXpW/fsPVIcOHbV+/Tq9//5Cde7cTZcv27V587dasGC+Ro8ep1q1amvdui8VHT1EH3+8Sn5+fpo8OU4nThzTzJnxyszMUFzceEkq8v6x2Ryy2+3KyLiocuVy8/SZTPk7OOGygDNr1iw1a9ZMbdu2varPy8vrqrBitVqdQeha/d7e3gWuw+FQiQQcXI39DKAsK6v/D8vJydbjjw/Wo4/2lclkUo0aNdW+fQcdOLBPa9d+rsaNm2rAgMGSpMGDh2nHju3OZT/66AP16/eEWre+8l395JP/0LZtW7R+/Vfq3Lm7Nm78l2bMmKeGDRtJkgYMGKxp094ottqL8h3tsoDz5ZdfKj09XWFhYZLkDCz//Oc/1b17d6Wnp+cZn56e7jwtVa1atb/sr1KlSilUDgBA2REYGKQuXbrr00+XKinpZx0/fkyHD/+s5s1DdeRIkho1apJnfLNmzfXrr79Kkk6cOKY5c2Zq/vzZzn6r1ark5JNKTj4hm82mW2+9zdnXuHHe93IllwWcDz/8UJcvX3a+fvPNNyVJI0eO1I4dO/Tuu+/K4XDIZDLJ4XBo165dGjZsmCQpNDRUCQkJioqKkiSlpqYqNTVVoaGhpb8hAAC4sbS0sxo8uJ8aNmysiIhIPfjg37V162bt27dXFotFUt5DJI4/HDKx2WwaMeI5RUS0yjOmQoUKOnMm9arxHh7lSm5DCshlAadmzZp5XleocGW+Su3atRUYGKi33npLcXFxevTRR/XJJ58oKytLXbp0kST16dNH/fr1U8uWLdW8eXPFxcWpffv2XCIOAMCffPvtRlWsWElTpkx3ti1f/qkkqU6detq7NzHP+EOHDqpGjSvf0SEhtZWWdlbBwf/7fp00aYL+9rf2CgsLl4eHhw4c2O8MQElJh0p4a/LPLW7092e+vr6aP3++8yhNYmKi4uPj5ePjI0kKCwvTq6++qtmzZ6tPnz6qVKmSJk+e7OKqAQBwP35+lfTLL2e0c+cPOn36lJYsWaxNmzbIarWqR48o7du3V0uWLNbJkyf0wQeLlJj4o/M2LY8+2lefffax1q37UqdPn9KcOTO0YcPXql27ripU8FXnzt00ffpU7dv3k3bt2qlFi+JdvLX/4/L74Pzu9ddfz/O6RYsWWrVq1TXHR0VFOU9RAQDganX867jlejp0uE+JiT9q3LgxMplMaty4iWJintHChfMVEBCoiRPf0KxZ07Vw4XzdcUek2rZtJw+PK/Hg3nvv1/nz57VgwTydP39edevW0xtvvK2QkFqSpGefHaW3356qZ5+NVsWKFdW796OaPXt6MW9x4ZgcjrI6L7x4pKeXzGXiHh5XLhPvO32tDp6+eZ+T1ahmgJY+010ZGRfd4rJKACis3Fyrzp1LVWBgdZUr979blZTlOxkfPXpYly9f1m23NXK2jRr1tBo1aqJBg4YWtcxCu9a+lq5cJh4U5MaXiQMAYAR2u0OZGVml+nwou91RLHcxPn36lCZPnqgJE+IUElJbO3ZsV0LCDg0dGlMMVboWAQcAgCIqrsBR2tq2ba+jR49o8uSJyszMUEhIbU2YMMl5p+KyjIADAMBN7PHHB+nxxwe5uoxi55ZXUQEAABQFAQcAgAK4ya/NKRXFsY8JOAAA5MOVu/5KVmuOiysxvt/3scVS+Jk0zMEBACAfzGaLvL19deFChiTJ09PLeUM8FA+HwyGrNUcXLmTI29tXZnPhj8MQcAAAyCc/vwBJcoYclAxvb1/nvi4sAg4AAPlkMplUqVKgKlb0l812+cYLoMAsFo8iHbn5HQEHAIACMpvNMps9bzwQLsMkYwAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDgEHAAAYDguDTgnTpzQoEGDFBYWpvbt22vBggXOvuTkZA0YMEAtW7ZU165dtXnz5jzLbt26Vd27d1doaKj69++v5OTk0i4fAAC4KZcFHLvdriFDhsjf31+rVq3ShAkTNHfuXK1Zs0YOh0PR0dEKCgrSihUr1KNHD8XExCglJUWSlJKSoujoaEVFRWn58uUKCAjQU089JYfD4arNAQAAbsTDVStOT09X48aNNX78ePn6+qpOnTq66667lJCQoKCgICUnJ+uTTz6Rj4+P6tevr23btmnFihUaPny4li1bpmbNmmngwIGSpMmTJ6t169b64YcfFBkZ6apNAgAAbsJlR3CqVq2q6dOny9fXVw6HQwkJCdqxY4datWqlxMRENWnSRD4+Ps7x4eHh2r17tyQpMTFRERERzj5vb281bdrU2Q8AAG5uLjuC80cdOnRQSkqK7rnnHnXq1EmTJk1S1apV84wJDAzUmTNnJElpaWnX7S8Ik6nwdaNg2NcAgKLK73eJWwScGTNmKD09XePHj9fkyZOVlZUlT0/PPGM8PT1ltVol6Yb9BREYWLHwhSPf/P0ruLoEAMBNxC0CTvPmzSVJOTk5GjlypHr16qWsrKw8Y6xWq8qXLy9J8vLyuirMWK1W+fn5FXjd5879ppKYm2yxmPlS/4OMjIuy2eyuLgMAUMaZTPk7OOHSSca7d+9Wx44dnW0NGjRQbm6uqlSpoqNHj141/vfTUtWqVVN6evpV/Y0bNy5wHQ6HSiTg4GrsZwBAaXHZJONTp04pJiZGv/zyi7Ptp59+UkBAgMLDw7Vv3z5lZ2c7+xISEhQaGipJCg0NVUJCgrMvKytL+/fvd/YDAICbm8sCTvPmzdW0aVO9+OKLOnz4sDZt2qSpU6dq2LBhatWqlapXr67Y2FglJSUpPj5ee/bsUe/evSVJvXr10q5duxQfH6+kpCTFxsYqODiYS8QBAIAkFwYci8WiOXPmyNvbW4888ojGjh2rfv36qX///s6+tLQ0RUVF6YsvvtDs2bNVo0YNSVJwcLBmzpypFStWqHfv3srMzNTs2bNl4jIdAAAgyeS4yW//m55eMpOMPTyuTDLuO32tDp4+X/wrKCMa1QzQ0me6KyPjoi5fZpIxAKBoTCYpKOjGk4x52CYAADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAct3jYJgCUNWazSWYzNxe12x2y22/q26nBTRFwAKCAzGaTKlf2kcXCQXCbza7MzEuEHLgdAg4AFJDZbJLFYta4j77TsbP/cXU5LlO3aiW99lhbmc0mAg7cDgEHAArp2Nn/3NSPYgHcGcdXAQCA4RQq4PTv31+//vrrVe3nz59XVFRUkYsCAAAoinyfovr222+1Z88eSdKOHTs0b948+fj45Blz4sQJnT59ungrBAAAKKB8B5y6detqwYIFcjgccjgc2rVrl8qVK+fsN5lM8vHxUVxcXIkUCgAAkF/5DjghISH64IMPJEmxsbEaO3asfH19S6wwAACAwirUVVSTJ0+WJKWlpeny5ctyOPJeHlijRo2iVwYAAFBIhQo4W7Zs0UsvvaTU1FRJksPhkMlkcv73wIEDxVokAABAQRQq4Lz66qtq0aKF5s6dy2kqAADgdgoVcM6cOaMFCxYoJCSkuOsBAAAoskLdByciIkIJCQnFXQsAAECxKNQRnDvuuEMTJkzQN998o9q1a+e5XFySYmJiiqU4AACAwij0JONmzZrp3LlzOnfuXJ4+k8lULIUBAAAUVqECzocffljcdQAAABSbQgWc1atXX7e/Z8+ehXlbAACAYlGogDNjxow8r202m86dOycPDw+1aNGCgAMAAFyqUAFnw4YNV7VdvHhRL7/8sho2bFjkogAAAIqiUJeJ/5UKFSpo+PDheu+994rrLQEAAAql2AKOJB08eFB2u7043xIAAKDACnWKql+/flddDn7x4kUdOnRIAwYMKI66AAAACq1QAScyMvKqNk9PT40cOVJ33XVXkYsCAAAoikIFnD/eqfjChQuy2WyqVKlSsRUFAABQFIUKOJL0/vvva8GCBUpPT5ckBQQEqE+fPjymAQAAuFyhAs7s2bO1ZMkSPf300woLC5PdbteuXbs0a9YseXp6asiQIcVdJwAAQL4VKuB89tlniouLU4cOHZxtjRs3VrVq1RQXF0fAAQAALlWoy8QvXLigOnXqXNVet25dnT9/vqg1AQAAFEmhAk5YWJgWLVqU5543NptNCxcuVIsWLYqtOAAAgMIo1Cmq2NhY9e3bV1u3blXTpk0lSfv27ZPVatWCBQuKtUAAAICCKlTAqV+/vl588UVlZmbq6NGj8vLy0saNGzVjxgw1atSouGsEAAAokEKdovrwww81fvx4VaxYUePHj1dsbKz69eunkSNH6rPPPivuGgEAAAqkUAHnvffe01tvvaW///3vzrYxY8Zo6tSpio+PL7biAAAACqNQAScjI0O1atW6qr1u3brOG/8BAAC4SqECTnh4uGbOnKmsrCxnW05OjubNm6ewsLBiKw4AAKAwCjXJ+OWXX9bAgQPVpk0b5/1wTp48qaCgIM2ZM6c46wMAACiwQgWcWrVq6auvvtJ3332n48ePy8PDQ3Xq1FGbNm1ksViKu0YAAIACKfTDNj09PXXvvfcWZy0AAADFolBzcAAAANwZAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABgOAQcAABiOSwPOL7/8ohEjRqhVq1Zq27atJk+erJycHElScnKyBgwYoJYtW6pr167avHlznmW3bt2q7t27KzQ0VP3791dycrIrNgEAALghlwUch8OhESNGKCsrS0uXLtXbb7+tjRs3avr06XI4HIqOjlZQUJBWrFihHj16KCYmRikpKZKklJQURUdHKyoqSsuXL1dAQICeeuopORwOV20OAABwIx6uWvHRo0e1e/dubdmyRUFBQZKkESNG6I033tDf/vY3JScn65NPPpGPj4/q16+vbdu2acWKFRo+fLiWLVumZs2aaeDAgZKkyZMnq3Xr1vrhhx8UGRnpqk0CAABuwmVHcKpUqaIFCxY4w83vLly4oMTERDVp0kQ+Pj7O9vDwcO3evVuSlJiYqIiICGeft7e3mjZt6uwHAAA3N5cdwfHz81Pbtm2dr+12u5YsWaI777xTaWlpqlq1ap7xgYGBOnPmjCTdsL8gTKZCFI9CYV8DxsXnG6Ulv//WXBZw/mzq1Knav3+/li9frsWLF8vT0zNPv6enp6xWqyQpKyvruv0FERhYsfBFI9/8/Su4ugQAJYTPN9yRWwScqVOn6v3339fbb7+t2267TV5eXsrMzMwzxmq1qnz58pIkLy+vq8KM1WqVn59fgdd97txvKom5yRaLmQ/9H2RkXJTNZnd1GUCx4POdF59vlCaTKX8HJ1wecCZOnKiPP/5YU6dOVadOnSRJ1apV0+HDh/OMS09Pd56WqlatmtLT06/qb9y4cYHX73CoRAIOrsZ+BoyLzzfcjUvvgzNr1ix98sknmjZtmrp16+ZsDw0N1b59+5Sdne1sS0hIUGhoqLM/ISHB2ZeVlaX9+/c7+wEAwM3NZQHnyJEjmjNnjp588kmFh4crLS3N+dOqVStVr15dsbGxSkpKUnx8vPbs2aPevXtLknr16qVdu3YpPj5eSUlJio2NVXBwMJeIAwAASS4MOP/+979ls9k0d+5ctWnTJs+PxWLRnDlzlJaWpqioKH3xxReaPXu2atSoIUkKDg7WzJkztWLFCvXu3VuZmZmaPXu2TEzjBwAAcuEcnCFDhmjIkCHX7K9du7aWLFlyzf527dqpXbt2JVEaAAAo43jYJgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBwCDgAAMBy3CDhWq1Xdu3fX9u3bnW3JyckaMGCAWrZsqa5du2rz5s15ltm6dau6d++u0NBQ9e/fX8nJyaVdNgAAcFMuDzg5OTl67rnnlJSU5GxzOByKjo5WUFCQVqxYoR49eigmJkYpKSmSpJSUFEVHRysqKkrLly9XQECAnnrqKTkcDldtBgAAcCMuDTiHDx/Www8/rJMnT+Zp//7775WcnKxXX31V9evX19ChQ9WyZUutWLFCkrRs2TI1a9ZMAwcO1K233qrJkyfr9OnT+uGHH1yxGQAAwM14uHLlP/zwgyIjI/Xss8+qZcuWzvbExEQ1adJEPj4+zrbw8HDt3r3b2R8REeHs8/b2VtOmTbV7925FRkYWqAaTqUibgAJgXwPGxecbpSW//9ZcGnAee+yxv2xPS0tT1apV87QFBgbqzJkz+eoviMDAigVeBgXn71/B1SUAKCF8vuGOXBpwriUrK0uenp552jw9PWW1WvPVXxDnzv2mkpi6Y7GY+dD/QUbGRdlsdleXARQLPt958flGaTKZ8ndwwi0DjpeXlzIzM/O0Wa1WlS9f3tn/5zBjtVrl5+dX4HU5HCqRgIOrsZ8B4+LzDXfj8quo/kq1atWUnp6epy09Pd15Wupa/VWqVCm1GgEAgPtyy4ATGhqqffv2KTs729mWkJCg0NBQZ39CQoKzLysrS/v373f2AwCAm5tbBpxWrVqpevXqio2NVVJSkuLj47Vnzx717t1bktSrVy/t2rVL8fHxSkpKUmxsrIKDgwt8BRUAADAmtww4FotFc+bMUVpamqKiovTFF19o9uzZqlGjhiQpODhYM2fO1IoVK9S7d29lZmZq9uzZMnGdIgAAkBtNMj506FCe17Vr19aSJUuuOb5du3Zq165dSZcFAADKILc8ggMAAFAUBBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4Hq4uAABQtlks/K0sSXa7Q3a7w9Vl4L8IOACAQgmsWF4Ou01+ft6uLsUt2G02ZWRmEXLcBAEHAFAoFct7ymS2KH3lC8pNP+rqclyqXFA9BUW9LrPZRMBxEwQcAECR5KYfVe6ZA64uA8iDE6cAAMBwCDgAAMBwCDgAAMBwmIODUsFlpFdwGSkAlA4CDkoUl5HmxWWkAFA6CDgoUVxG+j9cRgoApYeAg1LBZaQAgNLExAgAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4BBwAAGA4Hq4uALjZWCz8XWG3O2S3O1xdBgADI+AApcRcIVA2u01+ft6uLsXlbHabMjOyCDkASgwBBygl5vJ+spgtmvDPCTqecdzV5bhMHf86eqXTKzKbTQQcACWGgAOUsuMZx/Vz2s+uLgMADI3JAAAAwHAIOAAAwHAIOAAAwHAIOAAAwHAIOAAAwHC4igoAgGLCjTzd50aeZTrg5OTkaMKECVq/fr3Kly+vgQMHauDAga4uCwBwk+FGnv/jLjfyLNMBZ8qUKfrpp5/0/vvvKyUlRWPGjFGNGjXUuXNnV5cGALiJcCPPK9zpRp5lNuBcunRJy5Yt07vvvqumTZuqadOmSkpK0tKlSwk4AACX4Eae7qPMniw8ePCgLl++rLCwMGdbeHi4EhMTZbfbXVgZAABwtTJ7BCctLU3+/v7y9PR0tgUFBSknJ0eZmZkKCAjI1/uYzZKjBI+iNaoRIG/PMrubi6x2VT9JkuctjWUqd3Ofm/YIqitJui3oNpX3KO/ialynVuVazt/NZfZPrCv4fPP5/h2f7ytK4/NtMuVznMNRkl/vJWf16tV65513tHHjRmdbcnKyOnbsqE2bNumWW25xYXUAAMCVyuzfT15eXrJarXnafn9dvvzNm54BAEAZDjjVqlVTRkaGLl++7GxLS0tT+fLl5efn58LKAACAq5XZgNO4cWN5eHho9+7dzraEhAQ1b95c5rJ+Yh8AABRJmU0C3t7e6tmzp8aPH689e/boX//6lxYtWqT+/fu7ujQAAOBiZXaSsSRlZWVp/PjxWr9+vXx9fTVo0CANGDDA1WUBAAAXK9MBBwAA4K+U2VNUAAAA10LAAQAAhkPAAQAAhkPAAQAAhkPAAQAAhkPAAQAAhkPAgaGcOnVKDRs21Pr169WxY0c1b95cQ4cOVWZmpiTpxx9/VJ8+fdSyZUt16NBBH3/8sWsLBnBN48aN07Bhw/K0TZw4UaNGjVJqaqqGDRum0NBQdejQQbNmzZLNZpMk5ebmaty4cYqMjFRYWJiGDRumX375xRWbABci4MCQ5s2bp2nTpmnJkiXau3ev3nvvPR05ckSPP/647rjjDq1cuVLDhw/XG2+8oa+//trV5QL4C926ddOWLVt04cIFSZLdbtc///lPdevWTTExMQoMDNSqVas0efJkrVmzRvPmzZMkLV26VDt27NCiRYu0fPlyXbx4UZMmTXLlpsAFPFxdAFASRowYoRYtWkiSHnjgAe3du1fZ2dlq0qSJnnvuOUlSvXr1dOTIES1YsED33XefK8sF8BciIyNVqVIlbdiwQQ8++KB27typ3NxcWSwWpaSkaNmyZTKbzapXr57GjBmj2NhYRUdH69SpU/Ly8lLNmjVVuXJlvf76686juLh5EHBgSLVr13b+7uvrq9zcXB05csQZen4XFhamTz75pLTLA5APZrNZXbp00bp16/Tggw/q//7v/3TffffpxIkTyszMVHh4uHOs3W5Xdna2MjIy9Mgjj+jLL79UmzZt1KpVK3Xs2FFRUVEu3BK4AgEHhlSuXLmr2ry8vK5qs9vtzvP2ANxP9+7d1a9fP124cEFff/21pk6dqkOHDqlevXqaM2fOVeMrVqwof39/bdiwQd98842++eYbTZs2TWvXrtXSpUtlMplcsBVwBQIObhp169bVjh078rT9+OOPqlu3rosqAnAjoaGhqlatmt599105HA61atVKVqtVKSkpCggIUMWKFSVJW7Zs0cqVKzVlyhStXr1anp6e6tq1q7p06aLdu3frkUce0blz5xQUFOTiLUJpYZIxbhqPPfaYDhw4oGnTpunYsWNatWqVPvroI/Xt29fVpQG4jq5du+q9995T586dZbFY1KZNG9WsWVOjRo3SoUOHtHPnTr300kvy9vaWxWLRb7/9pri4OG3btk3Jyclas2aNbrnlFvn7+7t6U1CKCDi4adSoUUPz58/Xd999pwceeEBz587VCy+8oF69erm6NADX0bVrV+Xk5Khr166SJIvForlz58put+vhhx/W8OHD1a5dO40bN06S1LdvX/Xs2VOjRo1S165dtX//fs2dO1cWi8WVm4FSZnI4HA5XFwEAwLVs2bJFL730kv79738zhwb5xhwcAIBbOnv2rBISEjR//nz17t2bcIMC4RQVAMAt/fbbb3rxxRfl7++vJ554wtXloIzhFBUAADAcjuAAAADDIeAAAADDIeAAAADDIeAAAADDIeAAAADDIeAAKLNWrlypDh06SJK2b9+uhg0burgiAO6CgAPAEMLCwrR582ZXlwHATRBwABiCp6enqlSp4uoyALgJAg4At5eQkKA+ffooNDRULVu21JNPPqmzZ8/mGfPHU1TPPvusxowZk6f/+eef19ixYyVJqampGjZsmEJDQ9WhQwfNmjVLNputdDYGQKkg4ABwa7/99puGDh2q1q1ba+3atVq4cKFOnjyp+Pj4ay7TrVs3bdy4Ubm5uZIkq9WqjRs3qlu3bnI4HIqJiVFgYKBWrVqlyZMna82aNZo3b15pbRKAUkDAAeDWsrOz9dRTTyk6OlohISEKDw/X/fffr6SkpGsu87e//U12u13bt2+XJG3evFnly5dXZGSkvv/+e6WkpGjixImqV6+eIiMjNWbMGH3wwQeltUkASgFPEwfg1qpUqaKePXtq8eLFOnDggA4fPqxDhw7p9ttvv+Yynp6e6tixo9avX682bdpo/fr16tSpkywWi44cOaLMzEyFh4c7x9vtdmVnZysjI0P+/v6lsVkAShgBB4Bb++WXX9SrVy81bdpUd999tx5++GF98803SkxMvO5yXbt2VWxsrMaNG6cNGzZo9uzZkqTLly+rXr16mjNnzlXLVKxYsUS2AUDpI+AAcGtff/21KlWqpPnz5zvbPvzwQzkcjusud/fdd8tms+m9995T+fLlFRERIUmqW7euUlJSFBAQ4Aw0W7Zs0cqVKzVlypSS2xAApYo5OADcWuXKlZWSkqJt27YpOTlZ8fHxWr9+vaxW63WX8/Dw0P3336958+apc+fOMplMkqQ2bdqoZs2aGjVqlA4dOqSdO3fqpZdekre3tywWS2lsEoBSQMAB4Na6dOmiBx98UCNGjFCvXr20fft2jRkzRkeOHLlhyOnWrZsuXbqkbt26OdssFovmzp0ru92uhx9+WMOHD1e7du00bty4kt4UAKXI5LjRcV4AAIAyhiM4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcAg4AADAcP4/HWR+VmeCtskAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2: 分析年龄对存活率影响,结论: 年龄对存活率的影响没有明显的相关性\n",
    "def agelevel(age):\n",
    "    if age <=16:\n",
    "        return \"child\" # 青年\n",
    "    elif age >=60:\n",
    "        return 'aged' # 老年\n",
    "    else:\n",
    "        return \"midlife\" # 中年\n",
    "\n",
    "print(agelevel)\n",
    "titanic['age_level'] = titanic['age'].map(agelevel)\n",
    "print(titanic.head(n=10))\n",
    "sns.countplot(x=\"alive\",hue='age_level',data=titanic)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T16:57:05.897740Z",
     "iopub.status.busy": "2024-11-29T16:57:05.897740Z",
     "iopub.status.idle": "2024-11-29T16:57:06.030211Z",
     "shell.execute_reply": "2024-11-29T16:57:06.029513Z",
     "shell.execute_reply.started": "2024-11-29T16:57:05.897740Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3：分析舱位等级与存活率影响, 结论: vip一等舱存活率比较高\n",
    "sns.countplot(x=\"alive\",hue='class',data=titanic)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
